Determining overall network health and stability

ABSTRACT

A network health analyzer that analyzes health of a computer network may be implemented in accordance with an embodiment of the present invention. A network profile including an issue profile and one or more benchmarks appropriate for the network is determined. A set of numeric measures that is common to all issues in the issue profile is established. The network health analyzer collects data points pertaining to the operation of the network. Based on the data points, numeric values corresponding to the numeric measures may be calculated. In turn, health indexes for all issues in the issue profile may be determined. Based on these health indexes for the issues, an overall health rating may be determined.

CLAIM OF PRIORITY

This application claims domestic priority under 35 U.S.C. §120 as aContinuation of prior U.S. patent application Ser. No. 13/048,809, filedon Mar. 15, 2011, which in turn claims domestic priority under 35 U.S.C.§120 as a Continuation of prior U.S. patent application Ser. No.11/946,745, filed on Nov. 28, 2007, the entire contents of which arehereby incorporated by reference as if fully set forth herein. Theapplicant(s) hereby rescind any disclaimer of claim scope in the parentapplication(s) or the prosecution history thereof and advise the USPTOthat the claims in this application may be broader than any claim in theparent application(s).

TECHNICAL FIELD

The present disclosure relates generally to network communications andnetwork management.

BACKGROUND

The approaches described in this section could be pursued, but are notnecessarily approaches that have been previously conceived or pursued.Therefore, unless otherwise indicated herein, the approaches describedin this section are not prior art to the claims in this application andare not admitted to be prior art by inclusion in this section.

Typical network management and administration solutions focus onimproving network availability. Using such a network management andadministration solution, a service provider may monitor serviceavailability of its network in real-time or near real time and performcontrol actions on the network to enhance the service availability whenany service outage has been detected. Thus, if a direct network linkbetween New York and Tokyo is relatively congested, but if a networklink between New York and London, and a network link between London andTokyo have ample unused capacity, the service provider may re-route sometraffic between New York and Tokyo to an alternate route between NewYork and Tokyo by way of London. Clearly, the more such alternativeroutes are used, even though the network availability may be maintained,the less optimal the service may be (for example, large packet losses,long delays and unpredictable jitters may be associated with thealternative routes) and the more costly the network is to be maintained.Congestion in the original link (New York, Tokyo) and the delays in thealternative links (New York, London, Tokyo) represent degradation in theoverall network health, although there is no significant impact toavailability.

Thus, similar to a car that may not be in an optimal condition even ifit is able to run between point A and point B, a network is notnecessarily a healthy network even if it still carries traffic. Just asa car without outward symptoms may fail over time, a network withoutproactive monitoring may develop various problems over time.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings:

FIG. 1A and FIG. 1B illustrate example system embodiments operable toanalyze network health;

FIG. 2 illustrates an example network health analyzer;

FIG. 3 illustrates an example process flow; and

FIG. 4 illustrates a computer system.

DESCRIPTION OF EXAMPLE EMBODIMENTS

Techniques for analyzing and monitoring network health are described. Inthe following description, for the purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the present invention. It will be apparent, however, toone skilled in the art that the present invention may be practicedwithout these specific details. In other instances, well-knownstructures and devices are shown in block diagram form in order to avoidunnecessarily obscuring the present invention.

Embodiments are described herein according to the following outline:

-   -   1.0 General Overview    -   2.0 Structural and Functional Overview    -   3.0 Analyzing and Monitoring Network Health        -   3.1 Example Network Health Analyzer        -   3.2 Example Operations    -   4.0 Implementation Mechanisms—Hardware Overview    -   5.0 Extensions and Alternatives

1.0 General Overview

The needs identified in the foregoing Background, and other needs andobjects that will become apparent for the following description, areachieved in the present invention, which comprises, in one embodiment, asystem comprising a network health analyzer for analyzing health of acomputer network.

One objective for an operator of a computer network (such as a serviceprovider network) is how to ensure that a network is up and running in amanner that services are not disrupted, outages are minimized, andservice quality and commitment are assured, when the network generates alarge amount of noise traffic such as syslog messages emitted by variousapplications or systems in the network or when there are problems thatwill degrade the network into serious problems over time. Since acomputer network is an evolving complex of applications, services,devices and spans, detailed problem-by-problem analyses over an extendedperiod may contain too many non-comparable fine details to tell if anoverall health of the network is improving or deteriorating.

In some embodiments, the overall health of the network can berepresented by an overall health rating. Furthermore, rationales thatsupport the overall health rating are deduced on a set of issues that isappropriate for the profile of the network. The rationales also lead toprognosis as well as recommendations related to the network health.Thus, the operator of the network may make an informed decision aboutsome of the pressing issues facing the network and what can be doneabout them.

Such an overall health rating may be repeatedly determined over anextended time. Hence, the operator will be able to see whether thenetwork health is improving or deteriorating, whether recommendationswork or not, whether an issue that has been neglected or procrastinateddevelops into serious complications or not, etc., in a rational andcomparable manner.

As used herein, the term “network health” does not just mean networkavailability, but also includes, but is not limited to, the network'sability to restore to a sustainable state of healthy balance. Benchmarksdefining such a sustainable state of healthy balance (or a baselinehealth state) may be determined following an analysis of the computernetwork that results in a determination of an appropriate networkprofile. For example, for a network with a particular network profile,re-routing traffic may not cause any impact on network availability.Indeed, some amount of re-routing traffic may indicate the network isbeing efficiently used. However, extensive and/or prolonged re-routingmay indicate some issues that are manifested within or without thenetwork (for instance, latency that may cause signaling traffic toexperience relatively frequent timeout problems in a servicesubscriber's VoIP application). Therefore, even if network availabilityis not impacted, and/or even if a resultant issue impacts entitiesoutside the network, and/or even if there are no apparent symptoms,and/or even if there are only chronic service impact issues (but fewacute service impact issues), a proactive check is needed to determinewhether the network is operating in a healthy manner for its intendedpurposes.

In some embodiments, knowledge obtained from technical review of networkdesign, technical analysis of device performance and compliance data,syslog message reporting, or network operation monitoring may beanalyzed and stored in a database manually, and/or in a programmaticmanner. Based on this established and growing knowledge base, differentissue profiles that correspond to different network profiles may bedeveloped. As used herein, an “issue profile” may include, but is notlimited to, a list of issues, an array of issues, an issue tree, otherrepresentations of network issues, etc. Likewise, numeric measuresapplicable to an issue in an issue profile may also be established todetermine, for example, application criticality and the extent of impactof the issue. Recommendations to improve the network health with respectto one or more issues in the issue profile may also be placed in theknowledge base. These issue profiles, numeric measures andrecommendations are not static, or limited to specific areas, but rathercan be further evolved and expanded.

In some embodiments, once determined as appropriate for a network, anetwork profile may be associated with an issue profile described aboveand a definition of a baseline health state. The baseline health statecomprises a set of benchmarks. Data collected from the network may becompared with the set of benchmarks defining the baseline health state,resulting in one or more data points that may be used by the networkhealth analyzer described above to deduce the overall health rating. Forexample, deviations or degradations from these benchmark value rangesare considered as symptoms of the network being in a possibly unhealthystate. Thus, the more severe the deviations or degradations are, themore unhealthy the network is. In some embodiments, data pointsindicating compliances, deviations or degradations may be used to derivea number of risk indexes. Based on the risk indexes, an overall healthrating may be computed. In a particular embodiment, the larger a valueof the overall health rating is (say, on a scale of 1 through 10), theless the network's operation deviates from the baseline health state.

In some embodiments, the techniques for analyzing network healthdescribed herein may be implemented using one or more computer programsexecuting on a network infrastructure element, such as a switch, arouter, a multiplexer, etc., that is established in a network. In someembodiments, the techniques described herein may be implemented by anappliance computer system that is operatively and/or communicativelycoupled to a network infrastructure element, such as a switch, a router,a multiplexer, or an add-drop multiplexer. In some embodiments, thetechniques described herein may be implemented on a host computer systemthat is communicatively connected to a network. Thus, the embodimentsdescribed herein illustrate examples and are not restrictive.

2.0 Structural and Functional Overview

In an embodiment a system to analyze and monitor health of a computernetwork may be implemented in any type of computing device. For example,the functionality of the example system may be implemented as a set ofinstructions executed by a processor. Alternatively or additionally,such functionality may be implemented as hard-wired logic components,such as in an ASIC or an FPGA. The computer network that is monitoredand analyzed may be any type of computer network. The computer networkmay comprise switches, routers, bridges, hubs, end stations, wirelessaccess points, wireless devices, etc.

FIG. 1A illustrates an example system operable to analyze network healthof a computer network.

As shown in FIG. 1A, the system 100 comprises a network health analyzer102, a knowledge base 104, a user interface 106, and a network collector108 that collects data from a network 110 whose health is to be analyzedby network health analyzer 102. As illustrated in FIG. 1A, network datacollector 108 has multiple communication links 112 to monitored network110. Links 112 may use different physical interfaces or speeds ordistances (such as LAN, metro, or WAN links). Through links 112, networkdata collector 108 receives different types of data from the network110.

The data may include, but are not limited to, real time raw trafficdata, real time raw statistical data, non-real time (processed)statistical data, long-term trend data, provisioning data, configurationdata, control plane data, event and alarm data, etc. For example, thedata may include CPU usage, memory usage, end-to-end measurement datasuch as delays, jitter, packet loss, bit error rate, etc. The data fromthe network 110 may be periodically collected automatically. The datamay be collected as the data is spontaneously emitted or when the datais requested by the network health analyzer 102 or the network datacollector 108. Apart from the data collected from the network, sourcesof data other than the network may also be used to provide informationabout the network 110 to the network health analyzer 102.

The knowledge base 104 may store issue profiles for different networkprofiles. The system 100 may provide a user interface for consultants,network managers, administrators, or other authorized personnel toinput, enhance, modify, or delete an issue profile or other parameters(such as weight, criticality, etc.) and thresholds associated with theissue profile. The data stored in this knowledge base 104 may beprovided to the network health analyzer 102 for the purpose ofdetermining an appropriate health index of the network 110. Issueprofiles are further described below.

The user interface 106 may be used by the system to receive input forany parameters, thresholds, or adjustments of any parameters andthresholds in the issue profile, and may display the result of networkhealth analysis from the network health analyzer 102 to a user.

The network health analyzer 102 may communicate with other entities ofthe system (100) directly or indirectly through communication linksestablished among the network health analyzer and the other entities ofthe system. In addition, the network health analyzer may communicatewith the network 110 through the network data collector (108) or anotherentity that has one or more communication links with the network 110.

3.0 Analyzing and Monitoring Network Health 3.1 Example Network ProfileAnalyzer

As illustrated in FIG. 1B, a network profile analyzer 122 may beimplemented in system 100. The network profile analyzer (122) determinesan appropriate network profile 124 for the network (110). Thisdetermination may involve technical review of network design andtechnical analysis of device performance and compliance data, forexample. In some embodiments, users such as network experts, supportpersonnel and network operation personnel may provide inputs into thenetwork profile analyzer (122) through a user interface such as 106 ofFIG. 1A. As a result, these inputs may be received and used by thenetwork profile analyzer (122) in determining the appropriate networkprofile (124).

To determine the network profile (124), the network profile analyzer(122) may analyze network configuration and/or service configurationdata, subscriber information, etc. In some embodiments, the networkprofile analyzer determines a number of characteristics in one or morenetwork categories for the network (110). For example, one such networkcategory may be “places-in-network” (PIN). Possible characteristics forthis category may be “core”, “edge”, or “aggregation”. Thus, if thenetwork (110) is operated by a primary carrier at the core and used toprovide services to large enterprises, secondary carriers, thecharacteristic in this network category for the network (110) may be“core”.

Another network category may be “application services”. This categorypertains to what types of application services the network (110)provides. Possible characteristics for this category may be “video”,“voice”, “storage”, or “data center”. Thus, if customers uses thenetwork (110) to run video related applications such as videodistribution and streaming, the characteristic in this category for thenetwork (110) may be “video”.

One another network category may be “network services”. This categorypertains to what network services the network (110) provides to thecustomers. For example, where the customers run video-relatedapplications, the network (110) may provide QoS based network servicesand/or multicast services. As a result, the characteristic in thisnetwork category for the network (110) may be determined as acombination of QoS and Multicast.

Still another network category may be “transport”. This categorypertains to one or more types of transports used in the network (110),and may take one or more characteristics such as “IP routing”, “MPLS”,“ATM POS”, “Cable”, “Ethernet”, “Wireless”, etc. For example, if thenetwork (110) uses IP routing as transport to carry traffics from thecustomers, then the characteristic in this network category for thenetwork (110) is “IP routing”.

Yet another network category that may be used to characterize a networksuch as 110 of FIG. 1A, is “infrastructure”. This network categorypertains to what type of network elements, links, infrastructureelements the network (110) deploys. Some possible characteristics inthis category may be types of vendor-supplied devices that are deployedin the network (110) and take one or more characteristics, for thepurpose of illustration, “CRS”, “GSR”, “7600”, “7500” (which refer tocorresponding network elements commercially available from CiscoSystems, Inc., San Jose, Calif.). For example, where the network uses7600 as infrastructure network elements, the characteristic in thisnetwork category for the network (110) may be “7600”.

In some embodiments, network profile analyzer 122 is a part of thenetwork health analyzer (102). The result (i.e., network profile 124) ofanalysis performed by the network profile analyzer 122 may be stored ina network health database 126 (which, in a particular embodiment, mayalso be used by the network health analyzer 102 to store or retrievedata).

The network profile (124) may, but is not limited to, comprise one ormore network characteristics, a baseline health state 128 thatcorrespond to the network characteristics, and an issue profile (such as132 of FIG. 2) that correspond to the network characteristics. In thepresent example, the network characteristics for the network (110) maybe determined as “Core” for PIN, “Video” for Application Services,“Multicast and QoS” for Network Services, “IP routing” for Transport,“7600” for Infrastructure, etc. Accordingly, the baseline health state(128) may comprise a number of benchmarks for dynamic ones of thesenetwork characteristics. For example, while PIN may be a relative staticcharacteristic of the network, a network characteristic such as “Video”can be measured, for instance, by one or more IEEE parameters such asend-to-end jitter, end-to-end delay, end-to-end packet loss, etc. usingdata collected from the network (110). Similarly, the “Multicast”characteristic may be measured by number of video streams or IGMPlatency; the “QoS” characteristic may be measured by class and queueproperties such as queue depth, bandwidth utilization within a number oftraffic classes, packet drops, etc. The “IP routing” characteristic maybe measured by IGP optimization properties such as convergence, protocoltimers, number of routes, etc. The “7600” characteristic may be measuredby utilization properties such as CPU, memory, link usages, etc, byredundancy properties such as RP failover timers (NSF/SSO), or byperformance properties such as MTBF, etc.

For instance, given the measurement properties relevant to the networkcharacteristics as described above, the corresponding benchmarks forthese measuring parameters or properties may be set as jitter no morethan 30 ms; delay no more than 150 ms; and packet loss no more than 1%;IGMP latency no more than 250 ms; BGP keepalive interval no more than 10sec; OSPF hello interval between 10 and 30 sec; classes of service nomore than three; queue depth no more than x packets for a particularinterface, where x may be a suitable number in unit of bytes; CPUutilization no more than 60%; memory utilization no more than 60%; etc.

In some embodiments, a network data analyzer 130 uses these benchmarksdefined in the baseline health state (128) to determine whether the datacollected from the network (110) pertaining to network operation showsdeviations from these benchmarks. If there are deviations, the networkdata analyzer determines how serious these deviations are relative tothe acceptable ranges. Even if the data does not show a deviation for aparticular measurement property, the network data analyzer may determinehow close the acceptable range may be violated. The results of this dataanalysis performed by the network data analyzer (130) may be deviations(136 of FIG. 1B in the network health database) one or more data points(208 of FIG. 2) that may be used by the network health analyzer (102 ofFIG. 1A) to determine the overall health rating (134 of FIG. 2).

3.1 Example Network Health Analyzer

FIG. 2 illustrates an example network health analyzer. In an embodiment,a network health analyzer 102 may comprise a number of data componentsand logic components, a subset of which are illustrated in FIG. 2.

3.1.1 Rules and Issue Profile

Based on provisioning and configuration information collected from thenetwork 110 and rules 202 imported from the knowledge base 104, thenetwork health analyzer may initially determine the network profile. Forexample, the provisioning and configuration information may indicatethat the network 110 is formed by a number of network devices with highcapacity that are used to carry traffic over long distances for manyother smaller tributary networks. Based on the rules 202 and/or networkpatterning information from the knowledge base 104, the network healthanalyzer 102 may determine that the network 110 is of a core serviceprovider network profile. For example, this determination of aparticular network profile may be made by evaluating numbers, typesand/or locations of network elements deployed in the network 110.

Based on the network profile, a particular default issue profile fromthe knowledge base may be used to initially define a particular issueprofile 132. An issue profile is a representation of likely healthproblems in the network of that type.

In one embodiment, issues in a default issue profile for a core serviceprovider type of network include, but are not limited to, 1) latencycaused by traffic re-routing, 2) BGP packet malformation that may causecrashes in routing protocol operations, 3) incorrect unidirectional linkdetection (UDLD) configuration, 4) inadequate hardware failoverredundancy of core routers or other network devices, 5) frequent SPFchurns (in OSPF routing protocol operations), 6) memory overrun ingeneric routing protocol operations, 7) mistaken enablement of IPdirected broadcast, 8) express-forwarding-class packet drops in corenetwork devices, 9) lack of redundancy support for OSPF area borderrouters, 10) high CPU utilization in core network devices, etc.

The particular issue profile 132 may be further updated, deleted,modified, or otherwise refined, for example, by a user using a userinterface such as 106 of FIG. 1A. In such a case, some or all parametersand thresholds in the particular issue profile may be altered. Thenetwork health analyzer 102 may also accept input from the user foradding one or more specific issues for the network 110 and define anyparameters and thresholds associated with each of the specific issues.

3.1.2 Rules and Numeric Measures

As shown in FIG. 2, based in part on rules 202 imported from theknowledge base 104, the network health analyzer 102 may determine a setof numeric measures 206 that are to be used to evaluate impact of anyissue (defined in the issue profile) on operation of the network 110.For example, based on the rules 202 and/or network patterninginformation from the knowledge base 104, the network health analyzer 102may first select a particular default set of numeric measures for thenetwork 110 among a number of default sets of numeric measures stored inthe knowledge base 104. Subsequently, the particular default set ofnumeric measures from the knowledge base may be used to initially definea particular set of numeric measures 206.

For example, in one embodiment, a default set of numeric measures fromthe knowledge base may comprise 1) a weight factor (characterizing theimportance of an issue), 2) an extent-of-impact factor (measuring howmany devices or network spans are affected by an issue), 3) anapplication-criticality factor (measuring the importance ofapplications—hosted in the network—affected by an issue), 4) anetwork-region factor (related to the scope of the network affected byan issue, for example, whether the issue impacts core network region,distribution network region, edge network region, etc.), 5) astatistical-significance factor (indicating whether an issue is afrequently recurring issue, a sporadically recurring issue or anisolated event), 6) a workaround-effectiveness factor (measuring whetherthere is a workaround available and how effective such a workaround is),and 7) an X-factor (measuring an subjective perception of seriousness ofan issue based on empirical data collected for this and other networksand feedbacks from an customer operating this network and various othercustomers operating other networks).

The particular set of numeric measures 206 that is initially definedbased in part on the rules 202 may be further updated, deleted,modified, or otherwise refined, for example, by a user using a userinterface such as 106 of FIG. 1A. In such a case, some or all measuresin the particular set of numeric measures parameters of any such measuremay be altered. The network health analyzer 102 may also accept inputfrom the user for adding one or more specific numeric measures for thenetwork 110 and define any parameters (such as default values) andthresholds associated with each of the specific numeric measures.

3.1.3 Data Points and Numeric Values

Data points that represent compliances or deviations (136 of FIG. 1B)from the relevant benchmarks established for the network profile of thenetwork (110 of FIG. 1A) can be used to determine numeric values thatcorrespond to the particular set of numeric measures 206 for each issuein the issue profile 132.

For example, an issue in the issue profile 132 of the network 110 may belatency caused by traffic re-routing. Such traffic-re-routing (forexample, linking New York and Tokyo through London) may occur becausedirect link capacity between two points (i.e., between New York andTokyo) in the network has been under-provisioned. As a result, throughtraffic statistical data collected through the network data collector(108), the network health analyzer 102 may receive data pointsrepresenting deviation (136) from the established benchmarks. Forexample, the data points may indicate that an excessive amount of realtime service traffic (for example, packets, phone calls, messages, etc.,generated by subscribers and customers) has been overflown or re-routedover alternative routes.

Since the re-routing paths take time to set up, the data points mayindicate there is an excessive latency (that is deviated from a certainbenchmark value range) in effectuating alternative traffic flows or intransporting the overflown traffic. As an example, the network healthanalyzer 102 may determine that average latency for the re-routedservice traffic is 200 ms in the network 110, for example. Based on thisaverage latency, since 200-ms latency may cause many applications (forexample, signaling applications) to exceed some timer values that theseapplications are required to comply, the network health analyzer 102 maydetermine a corresponding value for the application-criticality measure.

Similarly, the network health analyzer 102 may determine, for the issueof latency caused by re-routed traffic, other values related to othernumeric measures other than the application-criticality measure. Forexample, for the issue of latency, the extent of impact (i.e., how manydevices and network spans are degraded) may be zero since the networkdevices and spans carrying the re-routed traffic may have sufficientcapacity to accommodate the re-routed traffic. Similarly, the networkhealth analyzer 102 may determine a network region type that the issueaffects the most. For example, the latency issue may affect mainly anedge region of the network. In this manner, values relating to the othernumeric measures (for example, in addition to the above, statisticalsignificance, workaround effectiveness, and X-Factor) may also bedetermined.

In some embodiments, computation of monitored data (such as computationof latency) may be performed in part or in whole by one or more externalentities to the network health analyzer 102. In such embodiments, thenetwork health analyzer 102 may collect the partial or full results(e.g., latency) of the computation from the one or more externalentities. As a result, the network health analyzer collects or acquiresone or more data points 208 about all the issues in the issue profile132.

Based on the data points collected and parameters/thresholds associatedwith an issue in the issue profile 132, the network health analyzer 102determines numeric values that correspond to the particular set ofnumeric measures 206 for the issue. In the present example, the issue islatency caused by re-routing. In one embodiment, the data point 208collected by the network health analyzer 102 allows the analyzer todetermine corresponding numeric values for most numeric measures in theset of numeric measures. For example, since application criticality ofthe latency issue is high, a numeric value of 50 in a set of discretevalues 10 (low criticality), (medium criticality), and 50 (highcriticality) may be assigned to the application-criticality factor.Likewise, since no network devices or spans are degraded, theextent-of-impact factor may be given a numeric value of 0. Furthermore,since the network region affected by the latency is the edge region,services provided to customers may be directly affected. Thus, a numericvalue of 30 in a set of discrete values 10 (core network region), 20(distribution network region), and 30 (edge network region) may beassigned to the network-region factor.

Parameters/thresholds that are associated with this issue as defined inthe issue profile 132 may also be used to determine correspondingnumeric values for the remaining numeric measures in the set of numericmeasures. For example, based on parameters/thresholds that areassociated with the latency issue, the numeric value of the weightfactor may be set to 5 in the range of 1 through 9. Other weight valuesand ranges may be used in other embodiments.

3.1.4 Risk Indexes and Network Health Indexes

Risk indexes 210 as shown in FIG. 2 are un-normalized numeric valuesthat each represent an impact of corresponding issue on operation of thenetwork 110. In one embodiment, a risk factor for a corresponding issuemay be computed by a formula. In one embodiment, a formula as shownbelow may be used to derive a risk factor for an issue:Risk Factor=(B+C+D+E+F*G)*H

In an embodiment, B is a weight factor. C is an extent-of-impact factor.D is an application-criticality factor. E is a network-region factor. Fis a statistical-significance factor, G is a workaround-effectivenessfactor, and H is an X-factor. Once numeric values for the abovementioned numeric measures are determined, risk factors for all theissues in the issue profile are determined based on the formula.

Network health indexes 212 as shown in FIG. 2 are normalized numericvalues, each of which represents a contribution of an associated issueto an overall health rating for the network 110. In one embodiment, anetwork health index for an issue may be derived based on a formula asfollows:Network Health index=(RI _(max) −RI)*RI _(max)/10

The network health index is for a particular issue, RI_(max) is themaximum value among all the risk indexes previously calculated, and RIis a risk index for the particular issue. For example, the issue ofexpress-forwarding-class packet drops in core network devices mayproduce a highest value, say 336, for a corresponding risk index amongall the risk indexes. On the other hand, a risk index, RI, for thelatency problem may have a numeric value of 115. Based on the aboveformula, therefore, a network health index for the latency problem mayhave a value of 7.69 on a scale of 0 through 10.

3.1.4 Overall Health Rating, Prognosis and Recommendation, andValidation

Once the network health indexes are determined, an overall health ratingas illustrated in 134 of FIG. 2 may be determined by averaging all thenetwork health indexes for all the issues in the issue profile.

The network health indexes 212, in combination with the rules 202imported from the knowledge base 104, may be used by the network healthanalyzer 102 to make a prognosis and recommendations (216) for health ofthe network 110 and for avoiding or lessening impacts from high priorityissues. For example, the network health analyzer 102 may determine thatthe latency issue, while important, is not the most urgent among all theissues. The network health analyzer may determine that the most criticalissue in the health of the network 110 is the issue relating to packetdrops for express forwarding services. The underlying reason may be thatthe express forwarding services are used by customers to runmission-critical operations. Through the rules 202 imported from theknowledge base 104 and data collected from the network 110, the networkhealth analyzer 102 may determine that, if the issue relating to expressforwarding services is solved, other issues may also be improved. Forexample, the re-routing latency issue may be indirectly caused bycongestion problems related to the express forwarding services.Therefore, once the express forwarding issue is resolved, the re-routinglatency issue may be significantly improved.

In some embodiments, the network health analyzer 102 continuesmonitoring the health of the network 110. Thus, the analysis leading tothe overall health rating for the network may be repeated from time totime. For example, such monitoring and analyzing may be conducted on adaily basis, weekly, seasonally, or yearly. The results from monitoringand analyzing may provide trend data for various risk indexes, networkhealth indexes, an overall health rating, or prognoses andrecommendations, individually or in combination.

Furthermore, validation 218 of the prognosis and recommendations 216 mayalso be implemented within the network health analyzer 102 to validatethe previously made prognosis (for example, if the recommendations werenot followed) and recommendations (for example, if the recommendationwere followed).

3.2 Example Operations

FIG. 3 illustrates an example process flow. To illustrate how networkhealth analysis can be provided by the network health analyzer 102 inone embodiment, an example, based on FIG. 1A and FIG. 2, is nowdescribed.

In block 302 of FIG. 3, the network health analyzer 102 determines anissue profile 132 of a particular computer network 110. The issueprofile comprises a set of one or more particular issues that affectoperation of the particular network 110. To illustrate a clear example,the particular computer network may be a service provider network. Insome embodiments, the one or more particular issues comprise at least anissue that does not immediately impact service availability of theparticular network. Rather, it may indicate that the network is notoperating in its most optimum condition.

In block 304 of FIG. 3, the network health analyzer 102 establishes aset of numeric measures. For example, a numeric measure in the set ofnumeric may measure 1) the extent of impact of an issue on the operationof the particular network, 2) application criticality of an issue in theparticular network, 3) location criticality of an issue in theparticular network, 4) statistical significance (frequent repetition,sporadic repetition, or isolated event) of an issue on the operation ofthe particular network, 5) effectiveness of workarounds, 6) a subjectiveweight of an issue that affects the operation of the particular network,etc.

The numeric measures established by the network health analyzer may becommon to all issues in the set of one or more particular issues in theissue profile. Furthermore, a numeric measure in the set of numericmeasures may have a value within an associated range of numeric values.The numeric measure with its value for an issue represents an amount ofimpact of the issue on the operation of the particular network.

In block 306 of FIG. 3, the network health analyzer 102 collects one ormore data points pertaining to the operation of the particular network.The one or more data points may be collected from the network 110 viathe network data collector 108. The one or more data points may includesuch data as real time raw traffic data, real time raw statistical data,non-real time (processed) statistical data, long-term trend data,provisioning data, configuration data, control plane data, event andalarm data, etc. Apart from the data collected from the network, sourcesof data other than the network may also be used to provide informationabout the network 110 to the network health analyzer 102.

Subsequently, the network health analyzer performs processing steps foreach issue in the set of one or more particular issues in the issueprofile. In block 308 of FIG. 3, the network health analyzer 102determines whether there is any issue yet to be processed. If so, blocks310 and 312 are performed for such an issue.

In block 310, the network health analyzer 102 calculates, based on theone or more data points collected from the particular network, a set ofnumeric values for the issue. Each numeric value in the set of numericvalues is associated with a numeric measure in the set of numericmeasures.

In block 312, based on the set of one or more numeric values for theissue, the network health analyzer determines a health index thatrepresents a contribution of the issue to an overall health rating.

If block 308 determines that all the issues have been processed, then atblock 314 the network health analyzer 102 determines correspondinghealth indexes individually for all the issues in the issue profile.

In some embodiments where the set of numeric measures comprises anextent-of-an impact factor, an application-criticality factor, alocation-criticality factor, a statistical-significance factor, aneffectiveness-of-workarounds factor, and a subjective-weight factor, ofthe issue; the network health analyzer 102 calculates a numeric sum ofthe extent-of-an impact factor, the application-criticality factor, thelocation-criticality factor, and a multiplicative product of thestatistical-significance factor and the effectiveness-of-workaroundsfactor, of the issue. The network health analyzer 102 then determines arisk factor of the issue. Such a risk factor may be determined as amultiplicative product of the numeric sum and the subjective-weightfactor in a particular embodiment.

The network health analyzer 102 may calculate the contribution of theissue to the overall health rating. For example, the network healthanalyzer 102 may determine a risk factor of the issue (for example, asdescribed above). This determination may be repeated for all the issuesin the issue profile to yield a plurality of risk factors. From theserisk factors, the network health analyzer 102 determines a highest riskfactor among issues. The network health analyzer 102 may compute a ratioof a difference between the risk factor of the issue and the highestrisk factor over the highest risk factor. The contribution of the issueto the overall health rating may be determined by the network healthanalyzer 102 as a multiplicative product of the ratio and a scalingfactor.

Thereafter, based on all health indexes that represent contributions ofall issues in the set of one or more issues, the network health analyzerdetermines, and subsequently stores, an overall health rating thatrepresents health of the particular network.

The above steps that determine the overall health rating may be repeatedfor one or more different times. For example, the steps may be repeatedperiodically so that trend information about the network health may beobtained and monitored.

4.0 Implementation Mechanisms—Hardware Overview

FIG. 4 illustrates a computer system 400 upon which embodiments of thetechniques for providing security for fiber-based communications may beimplemented. A preferred embodiment is implemented using one or morecomputer programs running on computer system 400, which is operativelycoupled to the backplane of a network infrastructure element such as,for example, a router or a switch.

Computer system 400 includes a bus 402 or other communication mechanismfor communicating information, and a processor 404 coupled with bus 402for processing information. Computer system 400 also includes a mainmemory 406, such as a random access memory (“RAM”) or other dynamicstorage device, coupled to bus 402 for storing information andinstructions to be executed by processor 404. Main memory 406 also maybe used for storing temporary variables or other intermediateinformation during execution of instructions to be executed by processor404. Computer system 400 further includes a read only memory (“ROM”) 408or other static storage device coupled to bus 402 for storing staticinformation and instructions for processor 404. A storage device 410,such as a magnetic disk or optical disk, is provided and coupled to bus402 for storing information and instructions.

Computer system 400 may be coupled via bus 402 to a display 412, such asa cathode ray tube (“CRT”), for displaying information to a computeruser. An input device 414, including alphanumeric and other keys, iscoupled to bus 402 for communicating information and command selectionsto processor 404. Another type of user input device is cursor control416, such as a mouse, trackball, stylus, or cursor direction keys forcommunicating direction information and command selections to processor404 and for controlling cursor movement on display 412. This inputdevice typically has two degrees of freedom in two axes, a first axis(e.g., x) and a second axis (e.g., y), that allows the device to specifypositions in a plane.

In one embodiment, computer system 400 is used for providing securityfor fiber-based communications. According to this embodiment, securityof fiber-based communications is provided by computer system 400 inresponse to processor 404 executing one or more sequences of one or moreinstructions contained in main memory 406. Such instructions may be readinto main memory 406 from another computer-readable medium, such asstorage device 410. Execution of the sequences of instructions containedin main memory 406 causes processor 404 to perform the process stepsdescribed herein. In alternative embodiments, hard-wired circuitry orother hardware-based logic may be used in place of or in combinationwith software instructions to implement the invention. Thus, embodimentsof the invention are not limited to any specific combination of hardwarecircuitry and software.

The term “computer-readable medium” as used herein refers to any mediumthat participates in providing instructions to processor 404 forexecution. Such a medium may take many forms, including but not limitedto, non-volatile media, volatile media, and transmission media.Non-volatile media includes, for example, optical or magnetic disks,such as storage device 410. Volatile media includes dynamic memory, suchas main memory 406. Transmission media includes coaxial cables, copperwire and fiber optics, including the wires that comprise bus 402.Transmission media can also take the form of acoustic or light waves,such as those generated during radio wave and infrared datacommunications.

Common forms of computer-readable media include, for example, a floppydisk, a flexible disk, hard disk, magnetic tape, or any other magneticmedium, a CD-ROM, any other optical medium, punch cards, paper tape, anyother physical medium with patterns of holes, a RAM, a PROM, and EPROM,a FLASH-EPROM, any other memory chip or cartridge, a carrier wave asdescribed hereinafter, or any other medium from which a computer canread.

Various forms of computer readable media may be involved in carrying oneor more sequences of one or more instructions to processor 404 forexecution. For example, the instructions may initially be carried on amagnetic disk of a remote computer. The remote computer can load theinstructions into its dynamic memory and send the instructions over atelephone line using a modem. A modem local to computer system 400 canreceive the data on the telephone line and use an infrared transmitterto convert the data to an infrared signal. An infrared detector canreceive the data carried in the infrared signal and appropriatecircuitry can place the data on bus 402. Bus 402 carries the data tomain memory 406, from which processor 404 retrieves and executes theinstructions. The instructions received by main memory 406 mayoptionally be stored on storage device 410 either before or afterexecution by processor 404.

Computer system 400 also includes a communication interface 418 coupledto bus 402. Communication interface 418 provides a two-way datacommunication coupling to a network link 420 that is connected to alocal network 422. For example, communication interface 418 may be anintegrated services digital network (“ISDN”) card or a modem to providea data communication connection to a corresponding type of telephoneline. As another example, communication interface 418 may be a localarea network (“LAN”) card to provide a data communication connection toa compatible LAN. Wireless links may also be implemented. In any suchimplementation, communication interface 418 sends and receiveselectrical, electromagnetic or optical signals that carry digital datastreams representing various types of information.

Network link 420 typically provides data communication through one ormore networks to other data devices. For example, network link 420 mayprovide a connection through local network 422 to a host computer 424 orto data equipment operated by an Internet Service Provider (“ISP”) 426.ISP 426 in turn provides data communication services through the worldwide packet data communication network now commonly referred to as the“Internet” 428. Local network 422 and Internet 428 both use electrical,electromagnetic or optical signals that carry digital data streams. Thesignals through the various networks and the signals on network link 420and through communication interface 418, which carry the digital data toand from computer system 400, are exemplary forms of carrier wavestransporting the information.

Computer system 400 can send messages and receive data, includingprogram code, through the network(s), network link 420 and communicationinterface 418. In the Internet example, a server 430 might transmit arequested code for an application program through Internet 428, ISP 426,local network 422 and communication interface 418. In accordance withthe invention, one such downloaded application provides for security forfiber-based communications as described herein.

The received code may be executed by processor 404 as it is received,and/or stored in storage device 410, or other non-volatile storage forlater execution. In this manner, computer system 400 may obtainapplication code in the form of a carrier wave.

5.0 Extensions and Alternatives

In the foregoing specification, the invention has been described withreference to specific embodiments thereof. It will, however, be evidentthat various modifications and changes may be made thereto withoutdeparting from the broader spirit and scope of the invention. Thespecification and drawings are, accordingly, to be regarded in anillustrative rather than a restrictive sense.

What is claimed is:
 1. A method, comprising: in a database, creating twoor more issue profiles each applicable to different network profileswith different characteristics wherein each of the different networkprofiles is for a different data communications network; determining,based at least in part on a network configuration of a particularnetwork, a particular network profile for the particular network,wherein the network configuration of the particular network includes anetwork characteristic pertaining to a type of application servicestraffic carried using the particular network, wherein the networkcharacteristic is determined using at least one of network parametersmeasuring end-to-end jitter, end-to-end delay, or end-to-end packet lossfor the particular network, and wherein the network characteristiccomprises one of a video characteristic, voice characteristic, storagecharacteristic, or a data center characteristic; selecting, from the twoor more issue profiles in the database, an issue profile for aparticular network, based at least in part on the particular networkprofile including the network characteristic, of the particular network;modifying the issue profile in response to receiving input thatspecifies removing or adding at least one issue to the issue profile,wherein the issue profile comprises a set of one or more particularissues that can affect operation of the particular network, and whereinat least one of the set of one or more particular issues does notimmediately impact service availability of the particular network;collecting one or more data points pertaining to the operation of theparticular network, wherein the one or more data points comprise a firstdata point, corresponding to a first network data type, which iscollected from the particular network using a first communication linkand a second data point, corresponding to a second network data type,which is collected from the particular network using a secondcommunication link; determining and storing, based on health indexesthat represent contributions of all issues in the set of one or moreparticular issues, an overall health rating that represents health ofthe particular network; wherein the method is performed by one or morecomputing devices.
 2. The method of claim 1, wherein at least one of thedata points represents either compliance or deviation from a benchmarkvalue range.
 3. The method of claim 1, further comprising establishing aset of numeric measures that is common to all issues in the set of oneor more particular issues in the issue profile, wherein a numericmeasure in the set of numeric measures comprises a value, for an issue,within an associated range of numeric values and wherein the numericmeasure represents an amount of impact of the issue on the operation ofthe particular network.
 4. The method of claim 1, further comprisingestablishing a set of numeric measures that is common to all issues inthe set of one or more particular issues in the issue profile, wherein anumeric measure in the set of numeric measures represents an extent ofan impact of the issue on the operation of the particular network. 5.The method of claim 1, further comprising establishing a set of numericmeasures that is common to all issues in the set of one or moreparticular issues in the issue profile, wherein a numeric measure in theset of numeric measures represents a location criticality of the issuein the particular network.
 6. The method of claim 1, further comprisingestablishing a set of numeric measures that is common to all issues inthe set of one or more particular issues in the issue profile, wherein anumeric measure in the set of numeric measures represents a statisticalsignificance of the issue on the operation of the particular network. 7.The method of claim 1, further comprising establishing a set of numericmeasures that is common to all issues in the set of one or moreparticular issues in the issue profile, wherein a numeric measure in theset of numeric measures represents an effectiveness of workarounds forthe issue that affects the operation of the particular network.
 8. Themethod of claim 1, further comprising establishing a set of numericmeasures that is common to all issues in the set of one or moreparticular issues in the issue profile, wherein the set of numericmeasures comprises an extent-of-an impact factor, anapplication-criticality factor, a location-criticality factor, astatistical-significance factor, an effectiveness-of-workarounds factor,and a subjective-weight factor, of the issue.
 9. The method of claim 1,wherein the contribution of an issue in the set of one or moreparticular issues to the overall health rating is calculated by:determining a risk factor of the issue; determining a highest riskfactor among issues in the issue profile; calculating a ratio of adifference between the risk factor of the issue and the highest riskfactor over the highest risk factor; and determining the contribution ofthe issue to the overall health rating as a multiplicative product ofthe ratio and a scaling factor.
 10. The method of claim 1, furthercomprising: for each issue in the set of one or more particular issuesin the issue profile: calculating, based on the one or more data pointscollected from the particular network, a set of numeric values;determining, based on the set of numeric values for the issue, thehealth index that represents a contribution of the issue to an overallhealth rating.
 11. A data processing system comprising: one or moreprocessors; a knowledge base configured to create two or more issueprofiles in a database, wherein each of the two or more issue profilesapplies to a different network profile with different characteristics; anetwork collector configured to collect one or more data pointspertaining to operation of a particular network, wherein the one or moredata points comprise a first data point, corresponding to a firstnetwork data type, which is collected from the particular network usinga first communication link and a second data point, corresponding to asecond network data type, which is collected from the particular networkusing a second communication link; and a network health analyzerconfigured to: determine, based at least in part on a networkconfiguration of the particular network, a particular network profilefor the particular network, wherein the network configuration of theparticular network includes a network characteristic pertaining to atype of application services traffic carried using the particularnetwork, wherein the network characteristic is determined using at leastone of network parameters measuring end-to-end jitter, end-to-end delay,or end-to-end packet loss for the particular network, and wherein thenetwork characteristic comprises one of a video characteristic, voicecharacteristic, storage characteristic, or a data center characteristic;select, from the two or more issue profiles stored in the database, anissue profile for the particular network, based at least in part on theparticular network profile including the network characteristic, of theparticular network; modify the issue profile in response to receivinginput that specifies removing or adding at least one issue to the issueprofile, wherein the issue profile comprises a set of one or moreparticular issues that can affect operation of the particular network,and wherein at least one of the set of one or more particular issuesdoes not immediately impact service availability of the particularnetwork; and determine and store, based on health indexes that representcontributions of all issues in the set of one or more particular issues,an overall health rating that represents health of the particularnetwork.
 12. The data processing system of claim 11, wherein at leastone of the data points represents either compliance or deviation from abenchmark value range.
 13. The data processing system of claim 11,wherein the network health analyzer is further configured to establish aset of numeric measures that is common to all issues in the set of oneor more particular issues in the issue profile, wherein a numericmeasure in the set of numeric measures comprises a value, for an issue,within an associated range of numeric values and wherein the numericmeasure represents an amount of impact of the issue on the operation ofthe particular network.
 14. The data processing system of claim 11,wherein the network health analyzer is further configured to establish aset of numeric measures that is common to all issues in the set of oneor more particular issues in the issue profile, wherein a numericmeasure in the set of numeric measures represents an extent of an impactof the issue on the operation of the particular network.
 15. The dataprocessing system of claim 11, wherein the network health analyzer isfurther configured to establish a set of numeric measures that is commonto all issues in the set of one or more particular issues in the issueprofile, wherein a numeric measure in the set of numeric measuresrepresents a location criticality of the issue in the particularnetwork.
 16. The data processing system of claim 11, wherein the networkhealth analyzer is further configured to establish a set of numericmeasures that is common to all issues in the set of one or moreparticular issues in the issue profile, wherein a numeric measure in theset of numeric measures represents a statistical significance of theissue on the operation of the particular network.
 17. The dataprocessing system of claim 11, wherein the network health analyzer isfurther configured to establish a set of numeric measures that is commonto all issues in the set of one or more particular issues in the issueprofile, wherein a numeric measure in the set of numeric measuresrepresents an effectiveness of workarounds for the issue that affectsthe operation of the particular network.
 18. The data processing systemof claim 11, wherein the network characteristic comprises anextent-of-an impact factor, an application-criticality factor, alocation-criticality factor, a statistical-significance factor, aneffectiveness-of-workarounds factor, and a subjective-weight factor, ofthe issue.
 19. The data processing system of claim 11, wherein thenetwork health analyzer is further configured to: determine a riskfactor of the issue; determine a highest risk factor among issues in theissue profile; calculate a ratio of a difference between the risk factorof the issue and the highest risk factor over the highest risk factor;and determine the contribution of the issue to the overall health ratingas a multiplicative product of the ratio and a scaling factor.
 20. Thedata processing system of claim 11, wherein the network health analyzeris further configured to: for each issue in the set of one or moreparticular issues in the issue profile: calculate, based on the one ormore data points collected from the particular network, a set of numericvalues; determine, based on the set of numeric values for the issue, thehealth index that represents a contribution of the issue to an overallhealth rating.